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<table width="100%" summary="page for ACF1"><tr><td>ACF1</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Aberrant Crypt Foci in Rat Colons</h2>

<h3>Description</h3>

<p>Numbers of aberrant crypt foci (ACF) in the 
section 1 of the colons of 22 rats subjected to a single
dose of the carcinogen azoxymethane (AOM), sacrificed
at 3 different times. 
</p>


<h3>Usage</h3>

<pre>ACF1</pre>


<h3>Format</h3>

<p>This data frame contains the following columns:
</p>

<dl>
<dt>count</dt><dd><p>The number of ACF observed in section 1 of
each rat colon</p>
</dd>
<dt>endtime</dt><dd><p>Time of sacrifice, in weeks following injection
of AOM</p>
</dd>
</dl>



<h3>Source</h3>

<p>Ranjana P. Bird, Faculty of Human Ecology, University of Manitoba,
Winnipeg, Canada.
</p>


<h3>References</h3>

<p>E.A. McLellan, A. Medline and R.P. Bird.  Dose response and
proliferative characteristics of aberrant crypt foci: putative
preneoplastic lesions in rat colon.  Carcinogenesis, 12(11): 2093-2098, 
1991.
</p>


<h3>Examples</h3>

<pre>
sapply(split(ACF1$count,ACF1$endtime),var)
plot(count ~ endtime, data=ACF1, pch=16)
pause()
print("Poisson Regression - Example 8.3")
ACF.glm0 &lt;- glm(formula = count ~ endtime, family = poisson, data = ACF1)
summary(ACF.glm0)

# Is there a quadratic effect?
pause()

ACF.glm &lt;- glm(formula = count ~ endtime + I(endtime^2),
  family = poisson, data = ACF1)
summary(ACF.glm)

# But is the data really Poisson?  If not, try quasipoisson:
pause()

ACF.glm &lt;- glm(formula = count ~ endtime + I(endtime^2),
  family = quasipoisson, data = ACF1)
summary(ACF.glm)
</pre>


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